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arize-instrumentation

Automate Arize AX tracing setup for LLM applications across Python, TypeScript, Java, and Go.

5|6|Updated Jun 28, 2026
Search Tags:#llm#observability#tracing#instrumentation#arize ax
One-click install
npx skills add https://github.com/seldo/aiewf-2026-demo --skill arize-instrumentation-seldo
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: arize-instrumentation
Source: https://github.com/seldo/aiewf-2026-demo/tree/main/.agents/skills/arize-instrumentation
Command: npx skills add https://github.com/seldo/aiewf-2026-demo --skill arize-instrumentation-seldo

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires arize-otel-go, openinference-instrumentation-openai-go, openinference-instrumentation-anthropic-sdk-go, openinference-semantic-conventions, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the setup of Arize AX tracing for LLM applications, simplifying the process of adding observability and monitoring to your application.

Core Features & Use Cases

  • Automated Tracing Setup: Handles the two-phase agent-assisted flow to analyze the codebase and implement instrumentation.
  • Compatibility: Supports Python, TypeScript/JavaScript, Java, and Go applications.
  • Use Case: Ideal for developers who want to integrate Arize AX tracing into their LLM applications to monitor and analyze performance.

Quick Start

Set up Arize AX tracing for your application using the arize-instrumentation skill.

Frequently Asked Questions about arize-instrumentation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I add LLM observability and tracing to my application?▼

To add LLM observability, you can automate Arize AX tracing setup to analyze your codebase and implement instrumentation, simplifying performance monitoring for LLM applications.

What languages does Arize AX tracing instrumentation support?▼

Arize AX tracing instrumentation supports Python, TypeScript/JavaScript, Java, and Go applications, providing both auto-instrumentation and manual span options for these languages.

How do I set up Arize AX tracing for my LLM application?▼

Set up Arize AX tracing by using an automated two-phase agent-assisted flow that analyzes your code and applies instrumentation, requiring your Arize API key and space ID to complete the setup.

Do I need an Arize API key to configure LLM tracing?▼

Yes, an Arize API key and space ID are required to configure LLM tracing and connect your application's observability data to the Arize AX platform.

Can I use auto-instrumentation for LLM tracing instead of manual spans?▼

Yes, you can use auto-instrumentation to automatically generate traces for your LLM application, or you can choose to manually create spans for custom observability needs.

What is the difference between auto-instrumentation and manual spans for LLM tracing?▼

Auto-instrumentation automatically captures standard LLM traces without code changes, while manual spans allow developers to define custom observability boundaries for specific application logic.

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